• Progress in Medical Physics
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• v.32 no.4
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• pp.116-121
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• 2021

Purpose: To investigate the effects of dose rate on intensity-modulated radiation therapy (IMRT) quality assurance (QA). Methods: We performed gamma tests using portal dose image prediction and log files of a multileaf collimator. Thirty treatment plans were randomly selected for the IMRT QA plan, and three verification plans for each treatment plan were generated with different dose rates (200, 400, and 600 monitor units [MU]/min). These verification plans were delivered to an electronic portal imager attached to a Varian medical linear accelerator, which recorded and compared with the planned dose. Root-mean-square (RMS) error values of the log files were also compared. Results: With an increase in dose rate, the 2%/2-mm gamma passing rate decreased from 90.9% to 85.5%, indicating that a higher dose rate was associated with lower radiation delivery accuracy. Accordingly, the average RMS error value increased from 0.0170 to 0.0381 cm as dose rate increased. In contrast, the radiation delivery time reduced from 3.83 to 1.49 minutes as the dose rate increased from 200 to 600 MU/min. Conclusions: Our results indicated that radiation delivery accuracy was lower at higher dose rates; however, the accuracy was still clinically acceptable at dose rates of up to 600 MU/min.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2044-2047
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• 2003

In this paper, we propose efficient motion vector refinement algorithm for frame-rate reduction transcoding. The proposed algorithm is to set the search range for motion refinement based on the incoming motion vector. The algorithm calculates the importance of motion vector of the skipped frame and then selects two motion vector to set search range. Through this process, we determine the accuracy of incoming motion vector and set the search range lot refinement adaptively by means of the accuracy. In experiments, we show efficiency of our algorithm to reduce the search points for refinement.

• Korean Journal of Clinical Pharmacy
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• v.17 no.1
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• pp.1-5
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• 2007

A computerized chemotherapy order system (CCOS) was developed to improve the accuracy and efficiency of prescriptions for pharmacy medication scheduling at a teaching hospital, Asan Medical Center, Seoul, Korea. We evaluated the system by comparing prescriptions before and after the implementation of the system and by analyzing the effects of the system on dosing accuracy (only against 5-FU), prescription change, overdoses above maximum limit and medication disposal in non computerized program group (control group) and CCOS group. In terms of dosing accuracy, prescription error rate (%) was significantly decreased in CCOS groups compared with the control group. The rate of prescription changes was also significantly decreased in CCOS groups. Regarding overdoses above maximum limit, we found that there was no prescription order exceeding the dosage limit in CCOS groups in contrast to significant overdoses in control group. In terms of medication disposal, there was no significant difference between 2 groups. We suggest that the computerized chemotherapy order system for chemotherapy may bean important and useful tool for minimizing prescribing errors in the hospitals.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.95-101
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• 2019

Recently, there have been many issues related to text recognition using Tesseract. One of these issues is that the text recognition accuracy is significantly lower for smaller fonts. Tesseract extracts text by creating an outline with direction in the image. By searching the Tesseract database, template matching with characters with similar feature points is used to select the character with the lowest error. Because of the poor text extraction, the recognition accuracy is lowerd. In this paper, we compared text recognition accuracy after applying various super-resolution methods to smaller text images and experimented with how the recognition accuracy varies for various image size. In order to recognize small Korean text images, we have used super-resolution algorithms based on deep learning models such as SRCNN, ESRCNN, DSRCNN, and DCSCN. The dataset for training and testing consisted of Korean-based scanned images. The images was resized from 0.5 times to 0.8 times with 12pt font size. The experiment was performed on x0.5 resized images, and the experimental result showed that DCSCN super-resolution is the most efficient method to reduce precision error rate by 7.8%, and reduce the recall error rate by 8.4%. The experimental results have demonstrated that the accuracy of text recognition for smaller Korean fonts can be improved by adding super-resolution methods to the OCR preprocessing module.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.330-337
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• 1995

For a rotating body with cracks, the new energy release rate equation is presented. The derived equation is different from the other researcher's results. It is a path-independent integral which excluded the derivatives of displacements near the crack tip, thereby improving the numerical accuracy of the energy release rate computation. Moreover, as the equation was derived on basis of the energy principle and non-linear elasticity without assumptions, it can applied to the cracked body with arbitrary shape under elastic-plastic deformation. Several examples are treated to demonstrate the efficiency and accuracy of the proposed method compared to existing methods.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.13-28
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• 2010

Assuming a mixture distribution for credit evaluation studies, we discuss estimating threshold methods to minimize errors that default borrowers are predicted as non defaults or non defaults are regarded as defaults. A method by using statistical hypotheses tests, the most powerful test and generalized likelihood ratio test, for the probability density functions which are defined with the score random variable and the parameter space consisted of only two elements such as the default and non default states is proposed to estimate a threshold. And anther optimal thresholds to maximize classification accuracy measures of the accuracy and the true rate for ROC and CAP curves are estimated as equations related with these probability density functions. Three kinds of optimal thresholds in terms of the hypotheses testing, the accuracy and the true rate are obtained from normal random samples with various means and variances. The sums of the type I and type II errors corresponding to each optimal threshold are obtained and compared. Finally we discuss about their efficiency and derive conclusions.

• Reproductive and Developmental Biology
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• v.35 no.3
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• pp.395-398
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• 2011

The objective of this study was to compare the accuracy analysis and the effect of field application of a newly developed automatic heat detector in dairy cows. From 2009 to 2010, we used 48 Holstein cows (mounting cows : 38 heads, standing cows : 10 heads) raised in experimental barn of National Livestock Research Institute (RDA) for the accuracy analysis of automatic heat detector, and 14 Holstein cows raised in three commercial dairy farms of Cheonan and Pochun area for comparison of the effect of field application. The accuracy of response in cows attached with automatic heat detector was 86.8% (33/38) displayed on board when mounting activity observed, and 100% (10/10) when standing activity observed, and on average, 90.0% (43/48) displayed on board. The accuracy of automatic heat detector in on-farm test was 85.7% (12/14), and conception rate was 75.0% (9/12).

• Journal of Korean Neurosurgical Society
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• v.63 no.6
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• pp.777-783
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• 2020

Objective : To compare the accuracy and breach rates of freehand (FH) versus navigated (NV) pedicle screws in the thoracic and lumbar spine in patients with metastatic spinal tumors. Methods : A retrospective review of adult patients who underwent pedicle screw fixation in the thoracic or lumbar spine for metastatic spinal tumors between 2012 and 2018 was conducted. Breaches were assessed based on the Gertzbein and Robbins classification and only screws placed >4 mm outside of the pedicle wall (lateral or medial) were considered breached. Results : A total of 62 patients received 547 pedicle screws (average 8 per patient) - 34 patients received 298 pedicle screws in the FH group and 28 patients received 249 screws in the NV group. There were 40/547 breaches, corresponding to a breach and accuracy rate of 7.3% and 92.7%, respectively. The breach rate was 9.7% in the FH group and 4.4% in the NV group (chi-squared test, p=0.017); this corresponded to an accuracy rate of 90.3% and 95.6%, respectively. Only one patient from the overall cohort (in the FH group) required revision surgery due to a medial breach abutting the spinal cord (1.6% of all patients; 2.9% of FH patients); no patient suffered organ, vessel, or neurological injury from screw breaches. Conclusion : Navigated pedicle screw placement in patients with metastatic spinal tumors has a significantly higher radiographic accuracy compared to the FH technique. However, the revision surgery was low and no patient suffered from clinically-relevant breach. Navigation also offers the advantage of real-time localization of spinal tumors and aids in targeting and resection of these lesions.

• The Korean Journal of Cytopathology
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• v.4 no.1
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• pp.1-8
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• 1993

This study was performed in order to evaluate the accuracy and the usefulness of the fine needle aspiration cytology (FNAC) on the breast lesions, to compare the FNAC findings between fibroadenoma and fibrocystic disease, and to determine the accuracy of cytologic Black's nuclear grading. The subjects in this study were 110 cases of FNAC, later confirmed by biopsy, between January 1988 and December 1991. The results are as follows ; 1 Comparison between the results of the FNAC and the histologic findings revealed that FNAC had a sensitivity of 96.6%, a specificity of 100%, a false negative rate of 3.4% a false positive rate of 0.0%, and an overall diagnostic accuracy of 98.2%. 2 Semi-quantitative evaluation of epithelial celluarity, stroma, and naked nuclei in the smears of aspirate showed high celluarity in 56.7% of the aspirates from fibroadenoma and in 0% of those from fibrocystic disease. Abundant stroma was found in 46.7% of the fibroadenoma and none of fibrocystic disease. Numerous naked nuclei were found in 60% of the fibroadenoma and 4.5% of the fibrocystic disease. The overall diagnostic accuracy was 98% 3. In order to determine the accuracy of Black's nuclear grading of FNAC on breast carcinoma, we retrospectively studied 38 cases of ductal carcinomas diagnosed by FNAC with subsequent histologic confirmation. The concordance rate with histology was 94.7%. These results suggest that FNAC of breast is a diagnostically accurate method, and provide for the preoperative differential diagnosis between fibroadenoma and fibrocystic disease. Our results also suggest that the evaluation of nuclear grading of FNAC can predict clinical outcome and decide the way of management of breast cancer.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.172-172
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• 2023

The use of low-cost IoT sensors for flow measurement in open channels has gained significant attention due to their potential to provide continuous and real-time data at a low cost. However, the accuracy and reliability of these sensors in real-world scenarios are not well understood. This study aims to compare the performance of low-cost IoT sensors in the laboratory and real-world conditions to evaluate their accuracy and reliability. Firstly, a low-cost IoT sensor was integrated with an IoT platform to acquire real-time flow rate data. The IoT sensors were calibrated in the laboratory environment to optimize their accuracy, including different types of low-cost IoT sensors (HC-SR04 ultrasonic sensor & YF-S201 sensor) using an open channel prototype. After calibration, the IoT sensors were then applied to a real-world case study in the Dorim-cheon stream, where they were compared to traditional flow measurement methods to evaluate their accuracy.The results showed that the low-cost IoT sensors provided accurate and reliable flow rate data under laboratory conditions, with an error range of less than 5%. However, when applied to the real-world case study, the accuracy of the IoT sensors decreased, which could be attributed to several factors such as the effects of water turbulence, sensor drift, and environmental factors. Overall, this study highlights the potential of low-cost IoT sensors for flow measurement in open channels and provides insights into their limitations and challenges in real-world scenarios.